# -*- coding: utf-8 -*-
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from datetime import timedelta
from jms.dm.route.cainiao_new_version.dm_cainiao_route_push_data_dt import jms_dm__dm_cainiao_route_push_data_dt

jms_dm__dm_route_cainiao_control_dt = SparkSqlOperator(
    task_id='jms_dm__dm_route_cainiao_control_dt',
    pool_slots=2,
    master='yarn',
    execution_timeout = timedelta(hours=1),
    email=['suning@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_route_cainiao_control_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/route/dm_route_cainiao_control_dt/execute.hql',
    driver_memory='5G' , 
    executor_memory='3G' , 
    executor_cores=2 , 
    num_executors=5 , 
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled' : 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors'             : 6 , 
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.sql.sources.partitionOverwriteMode' : 'dynamic',  # 允许删改已存在的分区
        'spark.executor.memoryOverhead'             : '2G' , 
        'spark.sql.shuffle.partitions' : 200,
    },
    #hiveconf={
    #    'hive.exec.dynamic.partition' : 'true',  # 动态分区
    #    'hive.exec.dynamic.partition.mode' : 'nonstrict',
    #    'hive.exec.max.dynamic.partitions' : 400,  # 每天生成 20 个分区
    #    'hive.exec.max.dynamic.partitions.pernode': 400,  # 每天生成 20 个分区
    #},
    yarn_queue='route',
)

jms_dm__dm_route_cainiao_control_dt << [
    jms_dm__dm_cainiao_route_push_data_dt
]
